From 3afb697d828b0a487ccad2e96aeb4618bcd1594d Mon Sep 17 00:00:00 2001 From: Toni Date: Wed, 13 Jul 2016 21:43:37 +0200 Subject: [PATCH 1/2] final competition --- competition/tex/chapters/abstract.tex | 2 +- competition/tex/chapters/barometer.tex | 2 +- competition/tex/chapters/components.tex | 2 +- competition/tex/chapters/introduction.tex | 7 +++---- competition/tex/chapters/performance.tex | 3 +-- competition/tex/egbib.bib | 2 +- 6 files changed, 8 insertions(+), 10 deletions(-) diff --git a/competition/tex/chapters/abstract.tex b/competition/tex/chapters/abstract.tex index 2e0c3b3..d736b5c 100644 --- a/competition/tex/chapters/abstract.tex +++ b/competition/tex/chapters/abstract.tex @@ -2,7 +2,7 @@ This technical description gives a short overview of the indoor localisation and navigation system developed at the University of Applied Sciences W\"urzburg-Schweinfurt and the University of Siegen, Germany. A highly modular system fusing different sensors, namely Wi-Fi, iBeacons, barometer, step- and turn-detection, will be shown. Additionally, extended knowledge provided by prior and past data is incorporate by natural walking paths and smoothing. -The system performs all calculations in real time on a commercial smartphone using a high number of particles. +The system performs all calculations in real time on a commercial smartphone using a high number of samples for approximation. \commentByFrank{particles? haben wir das hier schon eingefuehrt?} diff --git a/competition/tex/chapters/barometer.tex b/competition/tex/chapters/barometer.tex index 4fe6aca..9f81e19 100644 --- a/competition/tex/chapters/barometer.tex +++ b/competition/tex/chapters/barometer.tex @@ -1,6 +1,6 @@ \subsection{Barometer} - If available, the Smartphone's barometer is used to infer the likeliness of the current $z$-location. + If available, the smartphone's barometer is used to infer the likeliness of the current $z$-location. % As ambient pressure readings are highly influenced by environmental conditions like the weather, time-of-day and others \cite{Muralidharan14-BPS}, diff --git a/competition/tex/chapters/components.tex b/competition/tex/chapters/components.tex index 01528c5..0a46e76 100644 --- a/competition/tex/chapters/components.tex +++ b/competition/tex/chapters/components.tex @@ -20,7 +20,7 @@ By assuming statistical independence of all sensors, the probability density of \docIBeacon{}s and by $p(\vec{o}_t \mid \vec{q}_t)_\text{wifi}$ for \docWIFI{}. Compared to other state-of-the-art systems, step- and turn-detection are not incorporated into the evaluation step. - In our approach it stabilizes and improves the sampling of states $\vec{q}$ into moving more realistically. The transition step is the carried out using random walks on a graph, which is built offline, and uses the building's floorplan \cite{ebner-16}. + In our approach it stabilizes and improves the sampling of states $\vec{q}$ into moving more realistically. The transition step is then carried out using random walks on a graph, which is built offline, and uses the building's floorplan \cite{ebner-16}. \input{chapters/barometer.tex} diff --git a/competition/tex/chapters/introduction.tex b/competition/tex/chapters/introduction.tex index fa9c389..24b1189 100644 --- a/competition/tex/chapters/introduction.tex +++ b/competition/tex/chapters/introduction.tex @@ -4,11 +4,10 @@ The navigation system is based on our previous works, primarily on the approach For this, we have been awarded the best overall paper award at IPIN 2015 in Banff, Canada. Since then, we extended our approach by prior navigation knowledge using realistic human walking paths \cite{ebner-16} and smoothing methods \cite{fetzer-16}. Additionally, a self-developed map editor allows for creating advanced 3D maps and realistically shaped stairs. -Compared to many other systems, we avoid any time-consuming fingerprinting and calibration processes and are able to start with a uniform distribution over the whole building. -\commentByFrank{= we do not need any prior information on the pedestrian's starting position} +Compared to many other systems, we avoid any time-consuming fingerprinting and calibration processes. +Further, we do not need any prior information on the pedestrian's starting position. All calculations are computed in real time on a commercial smartphone, in most of our examples this is the Motorola Nexus 6 or the Samsung Galaxy S5. -The system is implemented in C++ using the Qt framework and OpenCL. -\commentByFrank{aktuell noch kein OpenCL leider} +The system is implemented in C++ using the Qt framework. \begin{figure} \centering diff --git a/competition/tex/chapters/performance.tex b/competition/tex/chapters/performance.tex index b6280a1..c8cd5aa 100644 --- a/competition/tex/chapters/performance.tex +++ b/competition/tex/chapters/performance.tex @@ -18,7 +18,7 @@ Starting uniformly distributed, the median error for all conducted walks are lis Additionally performing a smoothing step, would further improve the results and reduces temporal errors, as shown in \cite{fetzer-16}. % \begin{table}[h] - \caption{Median error for all conducted walks. \commentByFrank{without smoothing?}} + \caption{Median error for all conducted walks without smoothing. } \label{tbl:errNexus} \centering \begin{tabular}{|l|c|c|c|c|} @@ -29,4 +29,3 @@ Additionally performing a smoothing step, would further improve the results and \end{tabular} \end{table} - diff --git a/competition/tex/egbib.bib b/competition/tex/egbib.bib index 3e223ad..faf39fc 100644 --- a/competition/tex/egbib.bib +++ b/competition/tex/egbib.bib @@ -1574,7 +1574,7 @@ doi={10.1109/ICCKE.2013.6682841},} @inproceedings{Muralidharan14-BPS, author = {Muralidharan, Kartik and Khan, Azeem Javed and Misra, Archan and Balan, Rajesh Krishna and Agarwal, Sharad}, - title = {Barometric Phone Sensors: More Hype Than Hope!}, + title = {{Barometric Phone Sensors: More Hype Than Hope!}}, booktitle = {Proc. of the 15th Workshop on Mobile Computing Systems and Applications}, year = {2014}, isbn = {978-1-4503-2742-8}, From 388f58b93309bd7172dd9ce5fcb50e1271625eb7 Mon Sep 17 00:00:00 2001 From: Toni Date: Wed, 13 Jul 2016 21:44:19 +0200 Subject: [PATCH 2/2] final competition --- competition/tex/chapters/abstract.tex | 3 --- 1 file changed, 3 deletions(-) diff --git a/competition/tex/chapters/abstract.tex b/competition/tex/chapters/abstract.tex index d736b5c..076e3ff 100644 --- a/competition/tex/chapters/abstract.tex +++ b/competition/tex/chapters/abstract.tex @@ -3,8 +3,5 @@ This technical description gives a short overview of the indoor localisation and A highly modular system fusing different sensors, namely Wi-Fi, iBeacons, barometer, step- and turn-detection, will be shown. Additionally, extended knowledge provided by prior and past data is incorporate by natural walking paths and smoothing. The system performs all calculations in real time on a commercial smartphone using a high number of samples for approximation. -\commentByFrank{particles? haben wir das hier schon eingefuehrt?} - - \end{abstract} %\begin{IEEEkeywords} indoor positioning, Monte Carlo smoothing, particle smoothing, sequential Monte Carlo\end{IEEEkeywords}